An image reconstruction framework for characterizing initial visual encoding.

ABSTRACT: We developed an image-computable observer model of the initial visual encoding that operates on natural image input, based on the framework of Bayesian image reconstruction from the excitations of the retinal cone mosaic. Our model extends previous work on ideal observer analysis and evaluation of performance beyond psychophysical discrimination, takes into account the statistical regularities of the visual environment, and provides a unifying framework for answering a wide range of questions regarding the visual front end. Using the error in the reconstructions as a metric, we analyzed variations of the number of different photoreceptor types on human retina as an optimal design problem. In addition, the reconstructions allow both visualization and quantification of information loss due t

SUBMITTER: Zhang LQ 

PROVIDER: S-EPMC8846596 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature